Quantum Algorithms with Quantum Advantage

Silicon Quantum Computing (SQC) is an Australian research and development company, working to make quantum computers a reality. 

We are looking for a hard working, enthusiastic and dedicated student to join our team of expert researchers.  

Quantum algorithms have been shown to provide a way of speeding up certain computationally demanding classical algorithms, across an extensive range of problem types, including optimisation, solving linear algebra problems, solving differential equations and factoring large numbers. In recent years there has been a renewed effort to apply, adapt and extend previously developed quantum algorithms to solve real world problems across multiple industry types, including finance, chemistry, materials science, logistics, transport and pharmaceuticals. The ultimate aim in applying quantum algorithms to real world problems is to determine if, how and when a quantum advantage could be observed, given that we are currently working in the so-called noisy intermediate-scale quantum (NISQ) era. In this context, we define a quantum advantage to be when a quantum device could solve a practical problem faster, more efficiently, or with greater accuracy than that possible with the most powerful classical supercomputers. At SQC, we are developing the full stack platform for universal quantum computation based on high fidelity nuclear and electron spin qubit devices made from phosphorus donors in silicon. In this project we will develop quantum algorithms for the silicon based architecture to solve real world problems for industry that will lead to a provable near-term quantum advantage. This will include focusing on how best to use and minimise circuit depths for algorithms that rely on core workhorse quantum subroutines such as the quantum Fourier transform, amplitude amplification, quantum phase estimation, Hamiltonian simulation, quantum singular value transformation and quantum walks.    

How to Apply

Express your interest by emailing Dr Casey Myers at Casey.Myers@unsw.edu.au. Include a copy of your CV and your academic transcript(s).